ChartMogul to PlanetScale Integration
AI-first ETL from ChartMogul into PlanetScale. Governed entities, incremental sync, typed landing tables.
How Datrise loads ChartMogul into PlanetScale
Datrise syncs ChartMogul's customers, subscriptions, invoices, MRR movements, plans, and churn events into PlanetScale as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME.
Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Vitess sharding by tenant or entity key for very large tables. PlanetScale disallows foreign-key constraints by default, so Datrise models relationships by stable id columns rather than enforced FKs.
Ideal for horizontally scalable MySQL apps on Vitess.
Endpoints
ChartMogul: Subscription analytics and revenue reporting.
PlanetScale: Serverless MySQL platform with safe schema workflows.
How ChartMogul entities map to PlanetScale
| ChartMogul entity | PlanetScale object | Notes |
|---|---|---|
| customers | chartmogul_customers | id PK · custom fields → JSON columns |
| subscriptions | chartmogul_subscriptions | id PK · linked to chartmogul_customers |
| invoices | chartmogul_invoices | id PK · linked to chartmogul_customers |
| MRR movements | chartmogul_mrr_movements | DATETIME events |
FAQ
How does Datrise handle ChartMogul's custom fields in PlanetScale?
Flexible values are stored as JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PlanetScale types.
How does the ChartMogul to PlanetScale sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.
Related pipelines
More destinations for ChartMogul
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